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Updated: Jun 7, 2025

Non-invasive Assessment of the Efficacy of New Therapeutics for Intestinal Pathologies Using Serial Endoscopic Imaging of Live Mice
Published on: March 10, 2015
Comprehensive assessment of cellular senescence in intestinal immunity and biologic therapy response in ulcerative
Baojia Yao1, Yawei Zhang1, Qiang Wu1
1Department of General Surgery, The Second Xiangya Hospital of Central South University, Changsha, 410011, China.
Abstract:
Ulcerative Colitis (UC) is an inflammatory disorder characterized by chronic intestinal inflammation and immune dysregulation. Despite a clear association between cellular senescence and chronic inflammation and immune dysregulation, the mechanisms underlying cellular senescence in UC remain unclear. We screened differentially expressed genes (DEGs) associated with cellular senescence in multiple UC datasets, performed immune infiltration analysis, and constructed clinical diagnostic models. Additionally, we investigated the relationship between key genes related to cellular senescence and disease remission in UC patients undergoing biologic therapy, validating their expression in a single-cell dataset. We identified six DEGs associated with cellular senescence (TWIST1, IGFBP5, MME, IFNG, ME1, FOS). Immune infiltration results indicated strong correlations of four of these genes with immune cells and pathways. Through WGCNA, GO, and KEGG analyses, we found that gene modules strongly associated with the expression of hub genes in cellular senescence were enriched in inflammation-related pathways. In the single-cell dataset, the expression of these six key genes exhibited similarities with Immune infiltration results. Additionally, we constructed a nomogram using these six genes for diagnosing UC, demonstrating good diagnostic capability and clinical efficacy. Kaplan-Meier survival analysis revealed a significant association between changes in the expression levels of these cell genes and disease remission in UC patients undergoing biologic therapy. This study utilizes bioinformatic analysis and machine learning to identify and analyze features associated with cellular senescence in multiple UC datasets. It provides insights into the role of cellular senescence in the premature onset of intestinal aging in UC and offers new perspectives for exploring novel therapeutic targets.
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